In the past, airports have had difficulty getting historical and real-time information regarding the behaviour of passengers within and around an airport.
One solution to this problem is to use Bluetooth (Bluetooth is a registered trade mark of Bluetooth SIG, Inc, Washington, United States of America) or Radio Frequency Identification (RFID) tags. However these solutions have the following limitations:                RFID tags are not typically carried by passengers and therefore cannot be used without specifically issuing them to passengers.        Bluetooth is a short range protocol limited to small areas of the airport.        Bluetooth is not commonly active in passenger smart telephone devices, thereby limiting the accuracy of any measurements.        Bluetooth relies on Bluetooth Access Points in fixed locations. It is relatively complex and time consuming to relocate them if necessary.        
Another solution is to use a WiFi triangulation method to track passenger smart telephones. WiFi uses a wireless connection between a user device and an access point to transfer data between the user device and access point. WiFi is a registered trade mark of Wi-Fi Alliance, San Jose, United States of America. Usually, the access point has a wired connection to a local area network (LAN). However, a problem with this approach is that WiFi devices do not emit a continuous stream of data. This is because a device will only be detected when a user is actually using the airport WiFi infrastructure.
This means that for any given device, it may be detected only sporadically throughout the airport. For example, a device may be detected while a passenger is using their telephone in a café, or at a gate area, but not while walking from check in to security zones. This is of course problematic for live dwell time measurements because this sporadic data is not representative of what is actually happening in the airport.
Embodiments of the invention seek to address the above problems by using WiFi signals emitted through passenger smart telephones, and other devices, to provide location data which can be used to locate, track and measure the activities of passengers throughout the airport campus. The location data is processed to remove poor quality data and the remaining data is used to determine a passenger's path and associated dwell time information. This data can then be used to provide real time measurements for any section of the airport.
Embodiments of the invention, which may be referred to as and Indoor Anonymous Dwell Time Tracking system, are a multi component service that:
1. Allows airport staff to define arbitrary zones in the airport.
2. Locates devices using triangulation of WiFi signal strength.
3. Associates these devices to a zone in an airport.
4. Charts the path of devices in these spaces.
5. Maintains a live set of continuous device detections for devices detected in the airport
6. Uses this zone and device path data to determine the dwell time in any zones across the airport.
Embodiments of the invention improve on existing RFID systems because the passengers/consumers being tracked do not need to be given a RFID token to carry, and do not necessarily need to be informed that their movements are being tracked, which can subconsciously change behaviour.
Embodiments of the invention improve on Bluetooth systems because WiFi covers the entire airport campus, not just small specific areas. Therefore it is possible to provide sophisticated measurements such as “show current wait time for passengers in immigration who started in international arrivals”. It also improves on Bluetooth systems because the zones being measured are arbitrary and are not tied directly to the location of access points. In this regard, in a Bluetooth system, if an airport wants to modify the zone being measured, it is necessary to physically move the Bluetooth sensors. In the present invention, the airport staff just need to configure the new zone using a Google Map application.
Embodiments of the invention improve on basic WiFi triangulation because it can maintain a live device path, storing all the previous zones a device passed through, and use this data to determine if the data is suitable or not for live dwell time measurements.